MicroarrayDesigner: an online search tool and repository for near-optimal microarray experimental designs

<p>Abstract</p> <p>Background</p> <p>Dual-channel microarray experiments are commonly employed for inference of differential gene expressions across varying organisms and experimental conditions. The design of dual-channel microarray experiments that can help minimize the errors in the resulting inferences has recently received increasing attention. However, a general and scalable search tool and a corresponding database of optimal designs were still missing.</p> <p>Description</p> <p>An efficient and scalable search method for finding near-optimal dual-channel microarray designs, based on a greedy hill-climbing optimization strategy, has been developed. It is empirically shown that this method can successfully and efficiently find near-optimal designs. Additionally, an improved interwoven loop design construction algorithm has been developed to provide an easily computable general class of near-optimal designs. Finally, in order to make the best results readily available to biologists, a continuously evolving catalog of near-optimal designs is provided.</p> <p>Conclusion</p> <p>A new search algorithm and database for near-optimal microarray designs have been developed. The search tool and the database are accessible via the World Wide Web at <url>http://db.cse.ohio-state.edu/MicroarrayDesigner</url>. Source code and binary distributions are available for academic use upon request.</p

Stimulus-preceding negativity in ADHD

Children with ADHD often show disrupted response preparation as indicated by attenuated stimulus-preceding negativity (SPN). This study examined response preparation in a relatively short cue-stimulus interval. No differences in SPN occurred between children with ADHD and their normal peers. A strong positive relationship was found between SPN and mean reaction time in both groups. Children with ADHD are able to mentally prepare themselves for upcoming events in short cue-stimulus intervals. © 2013 Springer-Verlag Wien

Searching for phenotypic causal networks involving complex traits: an application to European quail

<p>Abstract</p> <p>Background</p> <p>Structural equation models (SEM) are used to model multiple traits and the casual links among them. The number of different causal structures that can be used to fit a SEM is typically very large, even when only a few traits are studied. In recent applications of SEM in quantitative genetics mixed model settings, causal structures were pre-selected based on prior beliefs alone. Alternatively, there are algorithms that search for structures that are compatible with the joint distribution of the data. However, such a search cannot be performed directly on the joint distribution of the phenotypes since causal relationships are possibly masked by genetic covariances. In this context, the application of the Inductive Causation (IC) algorithm to the joint distribution of phenotypes conditional to unobservable genetic effects has been proposed.</p> <p>Methods</p> <p>Here, we applied this approach to five traits in European quail: birth weight (BW), weight at 35 days of age (W35), age at first egg (AFE), average egg weight from 77 to 110 days of age (AEW), and number of eggs laid in the same period (NE). We have focused the discussion on the challenges and difficulties resulting from applying this method to field data. Statistical decisions regarding partial correlations were based on different Highest Posterior Density (HPD) interval contents and models based on the selected causal structures were compared using the Deviance Information Criterion (DIC). In addition, we used temporal information to perform additional edge orienting, overriding the algorithm output when necessary.</p> <p>Results</p> <p>As a result, the final causal structure consisted of two separated substructures: BW→AEW and W35→AFE→NE, where an arrow represents a direct effect. Comparison between a SEM with the selected structure and a Multiple Trait Animal Model using DIC indicated that the SEM is more plausible.</p> <p>Conclusions</p> <p>Coupling prior knowledge with the output provided by the IC algorithm allowed further learning regarding phenotypic causal structures when compared to standard mixed effects SEM applications.</p

Computational analysis of gene expression space associated with metastatic cancer

<p>Abstract</p> <p>Background</p> <p>Prostate carcinoma is among the most common types of cancer affecting hundreds of thousands people every year. Once the metastatic form of prostate carcinoma is documented, the majority of patients die from their tumors as opposed to other causes. The key to successful treatment is in the earliest possible diagnosis, as well as understanding the molecular mechanisms of metastatic progression. A number of recent studies have identified multiple biomarkers for metastatic progression. However, most of the studies consider only direct comparison between metastatic and non-metastatic classes of samples.</p> <p>Results</p> <p>We propose an alternative concept of analysis that considers the entire multidimensional space of gene expression and identifies the partition of this space in which metastatic development is possible. To apply this concept in cancer gene expression studies we utilize a modification of high-dimension natural taxonomy algorithm FOREL. Our analysis of microarray data containing primary and metastatic cancer samples has revealed not only differentially expressed genes, but also relations between different groups of primary and metastatic cancer. Metastatic samples tend to occupy a distinct partition of gene expression space. Further pathway analysis suggests that this partition is delineated by a specific pattern of gene expression in cytoskeleton remodeling, cell adhesion and apoptosis/cell survival pathways. We compare our findings with both report of original analysis and recent studies in molecular mechanism of metastasis.</p> <p>Conclusion</p> <p>Our analysis indicates a single molecular mechanism of metastasis. The new approach does not contradict previously reported findings, but reveals important details unattainable with traditional methodology.</p

Use of linear mixed models for genetic evaluation of gestation length and birth weight allowing for heavy-tailed residual effects

<p>Abstract</p> <p>Background</p> <p>The distribution of residual effects in linear mixed models in animal breeding applications is typically assumed normal, which makes inferences vulnerable to outlier observations. In order to mute the impact of outliers, one option is to fit models with residuals having a heavy-tailed distribution. Here, a Student's-<it>t </it>model was considered for the distribution of the residuals with the degrees of freedom treated as unknown. Bayesian inference was used to investigate a bivariate Student's-<it>t </it>(BS<it>t</it>) model using Markov chain Monte Carlo methods in a simulation study and analysing field data for gestation length and birth weight permitted to study the practical implications of fitting heavy-tailed distributions for residuals in linear mixed models.</p> <p>Methods</p> <p>In the simulation study, bivariate residuals were generated using Student's-<it>t </it>distribution with 4 or 12 degrees of freedom, or a normal distribution. Sire models with bivariate Student's-<it>t </it>or normal residuals were fitted to each simulated dataset using a hierarchical Bayesian approach. For the field data, consisting of gestation length and birth weight records on 7,883 Italian Piemontese cattle, a sire-maternal grandsire model including fixed effects of sex-age of dam and uncorrelated random herd-year-season effects were fitted using a hierarchical Bayesian approach. Residuals were defined to follow bivariate normal or Student's-<it>t </it>distributions with unknown degrees of freedom.</p> <p>Results</p> <p>Posterior mean estimates of degrees of freedom parameters seemed to be accurate and unbiased in the simulation study. Estimates of sire and herd variances were similar, if not identical, across fitted models. In the field data, there was strong support based on predictive log-likelihood values for the Student's-<it>t </it>error model. Most of the posterior density for degrees of freedom was below 4. Posterior means of direct and maternal heritabilities for birth weight were smaller in the Student's-<it>t </it>model than those in the normal model. Re-rankings of sires were observed between heavy-tailed and normal models.</p> <p>Conclusions</p> <p>Reliable estimates of degrees of freedom were obtained in all simulated heavy-tailed and normal datasets. The predictive log-likelihood was able to distinguish the correct model among the models fitted to heavy-tailed datasets. There was no disadvantage of fitting a heavy-tailed model when the true model was normal. Predictive log-likelihood values indicated that heavy-tailed models with low degrees of freedom values fitted gestation length and birth weight data better than a model with normally distributed residuals.</p> <p>Heavy-tailed and normal models resulted in different estimates of direct and maternal heritabilities, and different sire rankings. Heavy-tailed models may be more appropriate for reliable estimation of genetic parameters from field data.</p

Transcriptional analysis of abdominal fat in chickens divergently selected on bodyweight at two ages reveals novel mechanisms controlling adiposity: validating visceral adipose tissue as a dynamic endocrine and metabolic organ

Decades of intensive genetic selection in the domestic chicken (Gallus gallus domesticus) have enabled the remarkable rapid growth of today’s broiler (meat-type) chickens. However, this enhanced growth rate was accompanied by several unfavorable traits (i.e., increased visceral fatness, leg weakness, and disorders of metabolism and reproduction). The present descriptive analysis of the abdominal fat transcriptome aimed to identify functional genes and biological pathways that likely contribute to an extreme difference in visceral fatness of divergently selected broiler chickens. We used the Del-Mar 14 K Chicken Integrated Systems microarray to take time-course snapshots of global gene transcription in abdominal fat of juvenile [1-11 weeks of age (wk)] chickens divergently selected on bodyweight at two ages (8 and 36 wk). Further, a RNA sequencing analysis was completed on the same abdominal fat samples taken from high-growth (HG) and low-growth (LG) cockerels at 7 wk, the age with the greatest divergence in body weight (3.2-fold) and visceral fatness (19.6-fold). Time-course microarray analysis revealed 312 differentially expressed genes (FDR ≤ 0.05) as the main effect of genotype (HG versus LG), 718 genes in the interaction of age and genotype, and 2918 genes as the main effect of age. The RNA sequencing analysis identified 2410 differentially expressed genes in abdominal fat of HG versus LG chickens at 7 wk. The HG chickens are fatter and over-express numerous genes that support higher rates of visceral adipogenesis and lipogenesis. In abdominal fat of LG chickens, we found higher expression of many genes involved in hemostasis, energy catabolism and endocrine signaling, which likely contribute to their leaner phenotype and slower growth. Many transcription factors and their direct target genes identified in HG and LG chickens could be involved in their divergence in adiposity and growth rate. The present analyses of the visceral fat transcriptome in chickens divergently selected for a large difference in growth rate and abdominal fatness clearly demonstrate that abdominal fat is a very dynamic metabolic and endocrine organ in the chicken. The HG chickens overexpress many transcription factors and their direct target genes, which should enhance in situ lipogenesis and ultimately adiposity. Our observation of enhanced expression of hemostasis and endocrine-signaling genes in diminished abdominal fat of LG cockerels provides insight into genetic mechanisms involved in divergence of abdominal fatness and somatic growth in avian and perhaps mammalian species, including humans.https://doi.org/10.1186/s12864-017-4035-

Involvement of GABA(A)-benzodiazepine receptor in the anxiolytic effect induced by hexanic fraction of Rubus brasiliensis

To investigate the ability of hexanic ethanolic fraction of Rubus brasiliensis Martius (Roseceae), to induce anxiolytic effect and also the possible involvement of the GABA(A)-benzodiazepine receptor complex, male Wistar rats and Swiss mice behaviour were tested in the elevated plus maze (EPM). All the doses of the extract, 50, 100 and 150 mg/kg, administered per gavage (vo), 30 min before the behavioural evaluation, induced an anxiolytic effect expressed by: increased number of entries in and time spent in the open arms and percentage of open arm entries: and decreased number of entries and time spent in the closed arms. The treatment of mice with flumazenil (Ro 15-1788), 0.5, 1.0 and 1.5 mg/kg, i.p., 15-min before the administration of hexanic fraction, 100 mg/kg, vo, blocked the hexanic fraction-induced anxiolytic effect. The LD50 for the hexanic fraction was 1512 mg/kg. In conclusion, it was shown that the hexanic fraction of R. brasiliensis induced an anxiolytic effect in rats and mice. This effect can be attributed to a liposoluble principle with low toxicity which may be acting as an agonist on GABA(A)-benzodiazepine receptor complex. (C) 1998 Elsevier B.V. Ireland Ltd. All rights reserved

Pressão Arterial e Reatividade Vascular em Frangos de Corte Machos de Cinco Linhagens Comerciais

Blood pressure and vascular reactivity to phenylephrine (hypertensor) and sodium nitroprusside (hypotensor) was determined on male broilers taken from 5 commercial strains (Arbor Acres, Cobb, Hubbard-Peterson, ISA and Ross), with 21-28 days of age. Blood pressure was measured in the femoral artery by introducing a cannula attached to a pressure transdutor and recorded on a polygraph. Hyper or hypopressor substances were injected via jugular vein at 5, 10, 20 and 40-mcg kg(-1) body weight. No differences in the systolic, diastolic and mean blood pressure and no significant blood pressure responses to phenylephrine and sodium nitroprusside were observed among strains. Throughout strain and treatment blood pressures (systolic, diastolic and mean) were high in both experiments. This suggests that these modern male broilers have high arterial pressure possibly due to an indirect selection effect